Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: Heterogeneous catalysts are often & ldquo;black boxes & rdquo; due to the insufficient understanding of the detailed mechanisms at the catalytic sites. An atomic-level elucidation of the processes taking place in those regions is, thus, mandatory to produce robust and selective heterogeneous catalysts. We have improved the description of the whole reactive scenario for polymeric carbon nitrides (PCN) by combining atomic-level characterizations with magic-angle spinning (MAS) solid-state nuclear magnetic resonance (NMR) spectroscopy, classical reactive molecular dynamics (RMD) simulations, and quantum chemistry (QC) calculations. We disclose the structure & minus;property relationships of an ad hoc modified PCN by inserting an aryl amino group that turned out to be very efficient for the production of H2O2. The main advancement of this work is the development of a difluoromethylene-substituted aryl amino PCN to generate H2O2 at a rate of 2.0 mM & middot;h & minus;1 under the irradiation of household blue LEDs and the identification of possible active catalytic sites with the aid of 15N and 19F MAS solid-state NMR without using any expensive labeling reagent. RMD simulations and QC calculations confirm and further extend the experimental descriptions by revealing the role and locations of the identified functionalities, namely, NH linkers, & minus;NH2 terminal groups, and difluoromethylene units, reactants, and products. <comment>Superscript/Subscript Available</comment

Abstract: We present a computational model to model the magnetic structure of two-dimensional (2D) dilute-magnetic-semiconductors (DMS) both the monolayers and multilayers using first-principles density functional theory (DFT), as well as their magnetic phase transition as a function of temperature using Monte-Carlo simulations. Using our method, we model the magnetic structure of bulk, bilayer, and monolayer MoS2 substitutionally doped with Fe atoms. We find that the out-of-plane interaction in bilayer MoS2 is weakly ferromagnetic, whereas in bulk MoS2 it is strongly anti-ferromagnetic. Finally, we show that the magnetic order is more robust in bilayer Fe-doped MoS2 compared to the monolayer and results in a room-temperature FM at an atomic substitution of 14-16%.

Abstract: Targeting the redox balance of malignant cells via the delivery of high oxidative stress unlocks a potential therapeutic strategy against glioblastoma (GBM). We investigated a novel reactive oxygen species (ROS)-inducing combination treatment strategy, by increasing exogenous ROS via cold atmospheric plasma and inhibiting the endogenous protective antioxidant system via auranofin (AF), a thioredoxin reductase 1 (TrxR) inhibitor. The sequential combination treatment of AF and cold atmospheric plasma-treated PBS (pPBS), or AF and direct plasma application, resulted in a synergistic response in 2D and 3D GBM cell cultures, respectively. Differences in the baseline protein levels related to the antioxidant systems explained the cell-line-dependent sensitivity towards the combination treatment. The highest decrease of TrxR activity and GSH levels was observed after combination treatment of AF and pPBS when compared to AF and pPBS monotherapies. This combination also led to the highest accumulation of intracellular ROS. We confirmed a ROS-mediated response to the combination of AF and pPBS, which was able to induce distinct cell death mechanisms. On the one hand, an increase in caspase-3/7 activity, with an increase in the proportion of annexin V positive cells, indicates the induction of apoptosis in the GBM cells. On the other hand, lipid peroxidation and inhibition of cell death through an iron chelator suggest the involvement of ferroptosis in the GBM cell lines. Both cell death mechanisms induced by the combination of AF and pPBS resulted in a significant increase in danger signals (ecto-calreticulin, ATP and HMGB1) and dendritic cell maturation, indicating a potential increase in immunogenicity, although the phagocytotic capacity of dendritic cells was inhibited by AF. In vivo, sequential combination treatment of AF and cold atmospheric plasma both reduced tumor growth kinetics and prolonged survival in GBM-bearing mice. Thus, our study provides a novel therapeutic strategy for GBM to enhance the efficacy of oxidative stress-inducing therapy through a combination of AF and cold atmospheric plasma.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.